Bird Migration Group Project
Group Members: Veronika Kermoshchuk, Maria Coughlin, Sara Conway, Caitlin Larkin¶
#!pip install geopy --user codio
#!pip3 install haversine --user
!pip install geopy --user
!pip install haversine --user
Importing Libraries:¶
# Importing libraries
import pandas as pd
import matplotlib.pyplot as plt
from plotly import tools
import plotly as plt
import plotly.express as px
import chart_studio.plotly
from plotly.offline import init_notebook_mode, iplot
init_notebook_mode(connected=True)
import plotly.graph_objs as go
import plotly.figure_factory as ff
from IPython.display import HTML, Image
import plotly.express as px
px.set_mapbox_access_token(open(".mapbox_token").read())
from geopy.geocoders import Nominatim
import ipywidgets as widgets
from ipywidgets import interact, interact_manual
import haversine as hs
plt.offline.init_notebook_mode (connected = True)
import plotly.graph_objects as go
Data Set:¶
birds = pd.read_csv("bird_tracking.csv")
birds = birds.assign(date_time = lambda d: pd.to_datetime(d['date_time'], format = "%Y-%m-%d"))
birds['month'] = pd.to_datetime(birds['date_time']).dt.month
birds['hour'] = pd.to_datetime(birds['date_time']).dt.hour
birds.head()
Eric:¶
Eric = birds[birds['bird_name'] == "Eric"].reset_index()
Eric.head(2)
Nico:¶
Nico = birds[birds['bird_name'] == "Nico"].reset_index()
Nico.head(2)
Sanne:¶
Sanne = birds[birds['bird_name'] == "Sanne"].reset_index()
Sanne.reset_index().head(2)
Migration Pattern for Birds¶
bird_names = list(birds.bird_name.unique())
bird_names.append("ALL")
Note: This visual of the Eric's migration path is not available on GitHub because it GitHub does not support widgets.
@interact(birdName = bird_names)
def scatter_by_features(birdName):
if birdName == "ALL":
selected_df = birds
else:
selected_df = birds[birds.bird_name == birdName]
px.set_mapbox_access_token(open(".mapbox_token").read())
fig = px.scatter_mapbox(selected_df, lat="latitude", lon="longitude", color = "bird_name",
color_continuous_scale=px.colors.cyclical.IceFire, size_max= 5, zoom=3)
fig.show()
Note: This visual is not shown on the GitHub. See the html document on GitHub to see the visual.
px.set_mapbox_access_token(open(".mapbox_token").read())
fig = px.scatter_mapbox(birds, lat="latitude", lon="longitude", color = "bird_name",
color_continuous_scale=px.colors.cyclical.IceFire, size_max= 5, zoom=3)
fig.show()
For this project we used:¶
Departure month: August
Arrival month: April
Winter month: January/February
~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~¶
Migration Path of Eric¶
Note: There is a visual map of Eric's migration here but it is not showing up in GitHub. To see the visual please reference the html document on GitHub.
fig = px.scatter_mapbox(Eric, lat="latitude", lon="longitude", color = "bird_name",
color_continuous_scale=px.colors.cyclical.IceFire, size_max= 5, zoom=4)
fig.show()
Eric's Starting location:¶
Eric_lat_start = str(Eric['latitude'].iloc[0])
Eric_lon_start = str(Eric['longitude'].iloc[0])
geolocator = Nominatim(user_agent = 'geoapiExercises')
location = geolocator.reverse(Eric_lat_start+","+Eric_lon_start)
address = location.raw['address']
country = address.get('country', '')
country
Eric's starting location is France
Eric's location in January:¶
winter = Eric[Eric['month'] == 1].reset_index()
Eric_lat_winter = str(winter['latitude'].iloc[0])
Eric_lon_winter = str(winter['longitude'].iloc[0])
geolocator = Nominatim(user_agent = 'geoapiExercises')
location = geolocator.reverse(Eric_lat_winter+","+Eric_lon_winter)
address = location.raw['address']
country = address.get('country', '')
country
Eric's location during the winter month January is Morocco
Eric's ending location after migration:¶
Eric_lat_end = str(Eric['latitude'].iloc[Eric.shape[0]-1])
Eric_lon_end = str(Eric['longitude'].iloc[Eric.shape[0]-1])
geolocator = Nominatim(user_agent = 'geoapiExercises')
location = geolocator.reverse(Eric_lat_end+","+Eric_lon_end)
address = location.raw['address']
country = address.get('country', '')
country
Eric's ending location is Belgium after the migration
At the beginning Eric is located in France. Then during the cold months he migrates and stays at Morocco. Finally he returns in April and settles in Belgium after his migration.
Eric's first location in January¶
We used Eric's first location in January so that we can have one of the possible points of location where he is in Morocco.
first_loc = Eric[Eric['month'] == 1].head(1)
first_loc
The approximate distances that Eric traveled¶
loc1 = (float(Eric_lat_start), float(Eric_lon_start))
loc2 = (first_loc['latitude'].iloc[0], first_loc['longitude'].iloc[0])
to_dist = hs.haversine(loc1,loc2)
print("The distance that Eric traveled from France to Morocco is about:", round(hs.haversine(loc1,loc2),2), "KM")
loc1 = (first_loc['latitude'].iloc[0], first_loc['longitude'].iloc[0])
loc2 = (float(Eric_lat_end), float(Eric_lon_end))
from_dist = hs.haversine(loc1,loc2)
print("The distance that Eric traveled from Morocco to Belgium is about:", round(hs.haversine(loc1,loc2),2), "KM")
total_dist_Eric = to_dist + from_dist
print("The total distance that Eric traveled according to this dataset is about:", round(total_dist_Eric,2), "KM")
Migration Path of Nico¶
Note: There is a visual map of Nico's migration here but it is not showing up in GitHub. To see the visual please reference the html document on GitHub.
fig = px.scatter_mapbox(Nico, lat="latitude", lon="longitude", color = "bird_name",
color_continuous_scale=px.colors.cyclical.IceFire, size_max= 5, zoom=2)
fig.show()
Nico's Starting location:¶
Nico_lat_start = str(Nico['latitude'].iloc[0])
Nico_lon_start = str(Nico['longitude'].iloc[0])
geolocator = Nominatim(user_agent = 'geoapiExercises')
location = geolocator.reverse(Nico_lat_start+","+Nico_lon_start)
address = location.raw['address']
country = address.get('country', '')
country
Nico's starting location is Belgium
Nico's location in February:¶
winter = Nico[Nico['month'] == 2].reset_index()
Nico_lat_winter = str(winter['latitude'].iloc[0])
Nico_lon_winter = str(winter['longitude'].iloc[0])
geolocator = Nominatim(user_agent = 'geoapiExercises')
location = geolocator.reverse(Nico_lat_winter+","+Nico_lon_winter)
address = location.raw['address']
country = address.get('country', '')
country
Nico's location during the winter month February is Senegal, Africa
Nico's ending location after migration:¶
Nico_lat_end = str(Nico['latitude'].iloc[Nico.shape[0]-1])
Nico_lon_end = str(Nico['longitude'].iloc[Nico.shape[0]-1])
geolocator = Nominatim(user_agent = 'geoapiExercises')
location = geolocator.reverse(Nico_lat_end+","+Nico_lon_end)
address = location.raw['address']
country = address.get('country', '')
country
Nico's ending location is Belgium after migration
At the beginning Nico is located in Belgium. Then during the cold months he migrates and stays at Senegal. Finally he returns in April and settles in Belgium after his migration.
Nico's first location in February¶
first_loc_Nico = Nico[Nico['month'] == 2].head(1)
first_loc_Nico
The approximate distances that Nico traveled¶
loc1 = (float(Nico_lat_start), float(Nico_lon_start))
loc2 = (first_loc_Nico['latitude'].iloc[0], first_loc_Nico['longitude'].iloc[0])
to_dist_Nico = hs.haversine(loc1,loc2)
print("The distance that Nico traveled from Belgium to Senegal is about:", round(hs.haversine(loc1,loc2),2), "KM")
loc1 = (first_loc_Nico['latitude'].iloc[0], first_loc_Nico['longitude'].iloc[0])
loc2 = (float(Nico_lat_end), float(Nico_lon_end))
from_dist_Nico = hs.haversine(loc1,loc2)
print("The distance that Nico traveled from Senegal to Belgium is about:", round(hs.haversine(loc1,loc2),2), "KM")
total_dist_Nico = to_dist_Nico + from_dist_Nico
print("The total distance that Nico traveled according to this dataset is about:", round(total_dist_Nico,2), "KM")
Migration Path of Sanne¶
Note: There is a visual map of Sanne's migration path here but it is not showing up in GitHub. To see the visual please reference the html document on GitHub.
fig = px.scatter_mapbox(Sanne, lat="latitude", lon="longitude", color = "bird_name",
color_continuous_scale=px.colors.cyclical.IceFire, size_max= 5, zoom=2)
fig.show()
Sanne's Starting location:¶
Sanne_lat_start = str(Sanne['latitude'].iloc[0])
Sanne_lon_start = str(Sanne['longitude'].iloc[0])
geolocator = Nominatim(user_agent = 'geoapiExercises')
location = geolocator.reverse(Sanne_lat_start+","+Sanne_lon_start)
address = location.raw['address']
country = address.get('country', '')
country
Sanne's starting location is France
Sanne's location in January:¶
winter = Sanne[Sanne['month'] == 1].reset_index()
Sanne_lat_winter = str(winter['latitude'].iloc[0])
Sanne_lon_winter = str(winter['longitude'].iloc[0])
geolocator = Nominatim(user_agent = 'geoapiExercises')
location = geolocator.reverse(Sanne_lat_winter+","+Sanne_lon_winter)
address = location.raw['address']
country = address.get('country', '')
country
Sanne's location during the winter month January is Senegal, Africa
Sanne's ending location after migration:¶
Sanne_lat_end = str(Sanne['latitude'].iloc[Sanne.shape[0]-1])
Sanne_lon_end = str(Sanne['longitude'].iloc[Sanne.shape[0]-1])
geolocator = Nominatim(user_agent = 'geoapiExercises')
location = geolocator.reverse(Sanne_lat_end+","+Sanne_lon_end)
address = location.raw['address']
country = address.get('country', '')
country
Sanne's ending location is Belgium after migration
At the beginning Sanne is located in France. Then during the cold months he migrates and stays at Senegal. Finally he returns in April and settles in Belgium after his migration.
Sanne's first location in January¶
first_loc_Sanne = Sanne[Sanne['month'] == 1].head(1)
first_loc_Sanne
The approximate distances that Sanne traveled¶
loc1 = (float(Sanne_lat_start), float(Sanne_lon_start))
loc2 = (first_loc_Sanne['latitude'].iloc[0], first_loc_Sanne['longitude'].iloc[0])
to_dist_Sanne = hs.haversine(loc1,loc2)
print("The distance that Sanne traveled from France to Senegal is about:", round(hs.haversine(loc1,loc2),2), "KM")
loc1 = (first_loc_Sanne['latitude'].iloc[0], first_loc_Sanne['longitude'].iloc[0])
loc2 = (float(Sanne_lat_end), float(Sanne_lon_end))
from_dist_Sanne = hs.haversine(loc1,loc2)
print("The distance that Sanne traveled from Senegal to Belgium is about:", round(hs.haversine(loc1,loc2),2), "KM")
total_dist_Sanne = to_dist_Sanne + from_dist_Sanne
print("The total distance that Sanne traveled according to this dataset is about:", round(total_dist_Sanne,2), "KM")
Speed Differences Across All Birds¶
bird_mean_speed = birds.groupby('bird_name')['speed_2d'].mean().to_frame()
bird_mean_speed
Based on the information, Eric is the slowest bird since he has the lowest average speed compared to all the other birds. On the other hand Nico seems to be the fastest bird of all since he has the highest average speed.
Total Distance Traveled Across All Birds¶
print("Total distance traveled:")
print()
print("Eric:", round(total_dist_Eric,2))
print("Nico:", round(total_dist_Nico,2))
print("Sanne:", round(total_dist_Sanne,2))
Summary of the Results¶
Using the geopy library, our team was able to locate each birds location based on their longitude and latitude coordinates. Using this information, we focused on following the flight path and migration pattern for every bird. In addition to this information, our team also discovered the average speed of each bird and the total distance that each of them traveled.
Eric¶
Our team uncovered that Eric started his migration in France, flew to Morrocco during winter, and settled in Belgium after his migration in the spring.
The total distance of these three locations was also the shortest compared to the other two birds. Eric only traveled a total of 4884.99 KM. This is because the distance that Eric traveled from France to Morocco is about 2331.25 KM and the distance Eric traveled from Morocco to Belgium is about 2553.73 KM.
Furthermore, Eric proved to be the slowest bird as his average speed was only 2.300545 km/h.
It is interesting to note that Eric is the only bird that migrated to Morocco.
Nico¶
Our team uncovered that Nico started his migration in Belgium, flew to Senegal, Africa, during winter, and returned to Belgium after his migration in the spring.
The total distance of these three locations was also the second farthest compared to the other two birds. Nicco traveled a total of 8543.76 KM. This is because the distance that Nicco traveled from Belgium to Senegal, Africa, is about 4241.48 KM and the distance Nicco traveled from Senegal, Africa, to Belgium is about 4302.27 KM.
Furthermore, Nicco proved to be the fastest bird as his average speed was 2.908726 km/h.
It is interesting to note that Nico's migration route varied both times from his migration from Belgium to Senegal, Africa, and back.
Sanne¶
Our team uncovered that Sanne started his migration in France, flew to Senegal, Africa, during winter, and then flew to Belgium after his migration in the spring.
The total distance of these three locations was also the farthest compared to the other two birds. Sanne traveled a total of 8855.28 KM. This is because the distance that Sanne traveled from France to Senegal, Africa, is about 4343.33 KM and the distance Sanne traveled from Senegal, Africa, to Belgium is about 4511.95 KM.
Furthermore, Sanne's average speed was neither the fastest, nor slowest, as his average speed was 2.450434 km/h.
It is interesting to note that Sanne appears to fly a migration route that travels the most over ocean water compared to the other two birds.